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H2O

The "Awesome H2O" project is a curated collection of resources focused on H2O, an open-source distributed machine learning platform written in Java. H2O provides APIs in R, Python, and Scala, enabling users to build and deploy machine learning models efficiently. This list includes libraries, tutorials, documentation, community forums, and tools that facilitate the use of H2O for data analysis and predictive modeling. Whether you are a beginner looking to learn about machine learning or an experienced data scientist seeking advanced techniques, this collection offers valuable insights and resources. Dive into the world of machine learning with H2O and discover the tools to enhance your projects.

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Table of Contents

7 sections · 92 projects

Blog Posts & Tutorials

21 projects
Using H2O AutoML to simplify training process (and also predict wine quality)

enjoymachinelearning.com
Visualizing ML Models with LIME

uc-r.github.io
Parallel Grid Search in H2O

pavel.cool
Importing, Inspecting and Scoring with MOJO models inside H2O

pavel.cool
Artificial Intelligence Made Easy with H2O.ai: A Comprehensive Guide to Modeling with H2O.ai and AutoML in Python

towardsdatascience.com
Anomaly Detection With Isolation Forests Using H2O

dzone.com
Predicting residential property prices in Bratislava using recipes - H2O Machine learning

michal-kapusta.com
Inspecting Decision Trees in H2O

dzone.com
Gentle Introduction to AutoML from H2O.ai

medium.com
Machine Learning With H2O — Hands-On Guide for Data Scientists

dzone.com
Using machine learning with LIME to understand employee churn

business-science.io
Analytics at Scale: h2o, Apache Spark and R on AWS EMR

redoakstrategic.com
Automated and unmysterious machine learning in cancer detection

kkulma.github.io
Time series machine learning with h2o+timetk

business-science.io
Sales Analytics: How to use machine learning to predict and optimize product backorders

business-science.io
HR Analytics: Using machine learning to predict employee turnover

business-science.io
Autoencoders and anomaly detection with machine learning in fraud analytics

shiring.github.io
Building deep neural nets with h2o and rsparkling that predict arrhythmia of the heart

shiring.github.io
Predicting food preferences with sparklyr (machine learning)

shiring.github.io
Moving largish data from R to H2O - spam detection with Enron emails

ellisp.github.io
Deep learning & parameter tuning with mxnet, h2o package in R

blog.hackerearth.com

Books

10 projects
Big data in psychiatry and neurology, Chapter 11: A scalable medication intake monitoring system

elsevier.com
Hands on Time Series with R

www2.packtpub.com
Mastering Machine Learning with Spark 2.x

packtpub.com
Machine Learning Using R

amazon.com
Practical Machine Learning with H2O: Powerful, Scalable Techniques for Deep Learning and AI

amazon.com
Disruptive Analytics

link.springer.com
Computer Age Statistical Inference: Algorithms, Evidence, and Data Science

web.stanford.edu
R Deep Learning Essentials

packtpub.com
Spark in Action

manning.com
Handbook of Big Data

crcpress.com

Research Papers

43 projects
Automated machine learning: AI-driven decision making in business analytics

sciencedirect.com
Water-Quality Prediction Based on H2O AutoML and Explainable AI Techniques

mdpi.com
Which model to choose? Performance comparison of statistical and machine learning models in predicting PM2.5 from high-resolution satellite aerosol optical depth

sciencedirect.com
Prospective validation of a transcriptomic severity classifier among patients with suspected acute infection and sepsis in the emergency department

pubmed.ncbi.nlm.nih.gov
Depression Level Prediction in People with Parkinson’s Disease during the COVID-19 Pandemic

embc.embs.org
Maturity of gray matter structures and white matter connectomes, and their relationship with psychiatric symptoms in youth

onlinelibrary.wiley.com
Appendectomy during the COVID-19 pandemic in Italy: a multicenter ambispective cohort study by the Italian Society of Endoscopic Surgery and new technologies (the CRAC study)

pubmed.ncbi.nlm.nih.gov
Forecasting Canadian GDP Growth with Machine Learning

carleton.ca
Morphological traits of reef corals predict extinction risk but not conservation status

onlinelibrary.wiley.com
Machine Learning as a Tool for Improved Housing Price Prediction

openaccess.nhh.no
Citizen Science Data Show Temperature-Driven Declines in Riverine Sentinel Invertebrates

pubs.acs.org
Predicting Risk of Delays in Postal Deliveries with Neural Networks and Gradient Boosting Machines

diva-portal.org
Stock Market Analysis using Stacked Ensemble Learning MethodStock Market Analysis using Stacked Ensemble Learning Method

Compares stacked ensemble learning against individual ML algorithms for stock market trend prediction using Python.

#ensemble-learning#data-science#classification
Stars1
Forks0
Last commit6 years ago
H2O AutoML: Scalable Automatic Machine Learning

automl.org
Single-cell mass cytometry on peripheral blood identifies immune cell subsets associated with primary biliary cholangitis

nature.com
Prediction of the functional impact of missense variants in BRCA1 and BRCA2 with BRCA-ML

ncbi.nlm.nih.gov
Innovative deep learning artificial intelligence applications for predicting relationships between individual tree height and diameter at breast height

doi.org
An Open Source AutoML Benchmark

automl.org
Machine Learning in Python: Main developments and technology trends in data science, machine learning, and artificial intelligence

arxiv.org
Human actions recognition in video scenes from multiple camera viewpoints

sciencedirect.com
Extending MLP ANN hyper-parameters Optimization by using Genetic Algorithm

ieeexplore.ieee.org
askMUSIC: Leveraging a Clinical Registry to Develop a New Machine Learning Model to Inform Patients of Prostate Cancer Treatments Chosen by Similar Men

doi.org
Machine Learning Methods to Perform Pricing Optimization. A Comparison with Standard GLMs

variancejournal.org
Comparative Performance Analysis of Neural Networks Architectures on H2O Platform for Various Activation Functions

arxiv.org
Algorithmic trading using deep neural networks on high frequency data

link.springer.com
Generic online animal activity recognition on collar tags

dl.acm.org
Soil nutrient maps of Sub-Saharan Africa: assessment of soil nutrient content at 250 m spatial resolution using machine learning

link.springer.com
Robust and flexible estimation of data-dependent stochastic mediation effects: a proposed method and example in a randomized trial setting

arxiv.org
Automated versus do-it-yourself methods for causal inference: Lessons learned from a data analysis competition

arxiv.org
Using deep learning to predict the mortality of leukemia patients

qspace.library.queensu.ca
Use of a machine learning framework to predict substance use disorder treatment success

journals.plos.org
Ultra-wideband antenna-induced error prediction using deep learning on channel response data

kn.e-technik.tu-dortmund.de
Inferring passenger types from commuter eigentravel matrices

tandfonline.com
Deep neural networks, gradient-boosted trees, random forests: Statistical arbitrage on the S&P 500

sciencedirect.com
Identifying IT purchases anomalies in the Brazilian government procurement system using deep learning

ieeexplore.ieee.org
Predicting recovery of credit operations on a Brazilian bank

ieeexplore.ieee.org
Deep learning anomaly detection as support fraud investigation in Brazilian exports and anti-money laundering

ieeexplore.ieee.org
Deep learning and association rule mining for predicting drug response in cancer

doi.org
The value of points of interest information in predicting cost-effective charging infrastructure locations

rsm.nl
Adaptive modelling of spatial diversification of soil classification units. Journal of Water and Land Development

degruyter.com
Scalable ensemble learning and computationally efficient variance estimation

stat.berkeley.edu
Superchords: decoding EEG signals in the millisecond range

doi.org
Understanding random forests: from theory to practiceUnderstanding random forests: from theory to practice

A comprehensive PhD dissertation providing an in-depth theoretical and practical analysis of random forests, from algorithmic foundations to interpretability.

#ensemble-methods#random-forests#algorithm-analysis
Stars527
Forks154
Last commit10 years ago

Benchmarks

3 projects
Are categorical variables getting lost in your random forests?

roamanalytics.com
Deep learning in R

rblog.uni-freiburg.de
Szilard's machine learning benchmarkSzilard's machine learning benchmark

A minimal benchmark comparing scalability, speed, and accuracy of popular open-source machine learning libraries for binary classification.

#h2o#random-forest#open-source
Stars1,895
Forks327
Last commit4 years ago

Presentations

2 projects
Pipelines for model deployment

slideshare.net
Machine learning with H2O.ai

speakerdeck.com

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